Xiwei Mi

2.8k total citations · 2 hit papers
29 papers, 2.2k citations indexed

About

Xiwei Mi is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Environmental Engineering. According to data from OpenAlex, Xiwei Mi has authored 29 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Electrical and Electronic Engineering, 8 papers in Artificial Intelligence and 8 papers in Environmental Engineering. Recurrent topics in Xiwei Mi's work include Energy Load and Power Forecasting (18 papers), Solar Radiation and Photovoltaics (7 papers) and Traffic Prediction and Management Techniques (6 papers). Xiwei Mi is often cited by papers focused on Energy Load and Power Forecasting (18 papers), Solar Radiation and Photovoltaics (7 papers) and Traffic Prediction and Management Techniques (6 papers). Xiwei Mi collaborates with scholars based in China and Hong Kong. Xiwei Mi's co-authors include Hui Liu, Yanfei Li, Yanfei Li, Yan-fei Li, Chengqing Yu, Shuo Zhao, Guangxi Yan, Zhu Duan, Yinan Xu and Chengming Yu and has published in prestigious journals such as Journal of Cleaner Production, Energy Conversion and Management and IEEE Access.

In The Last Decade

Xiwei Mi

26 papers receiving 2.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM

2018 387 citations Hui Liu, Xiwei Mi et al. Energy Conversion and Management profile →
Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network

2017 385 citations Hui Liu, Xiwei Mi et al. Energy Conversion and Management profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Xiwei Mi China	18	1.7k	751	381	351	349	29	2.2k
Ping Jiang China	26	1.8k 1.1×	757 1.0×	276 0.7×	713 2.0×	379 1.1×	44	2.5k
Pei Du China	23	1.7k 1.0×	754 1.0×	277 0.7×	698 2.0×	381 1.1×	35	2.4k
Tong Niu China	27	1.8k 1.1×	816 1.1×	257 0.7×	783 2.2×	404 1.2×	47	2.7k
Wendong Yang China	30	2.2k 1.3×	969 1.3×	363 1.0×	1.1k 3.0×	527 1.5×	50	3.3k
Minas C. Alexiadis Greece	15	1.7k 1.0×	549 0.7×	381 1.0×	161 0.5×	208 0.6×	36	2.0k
Zi Lin United Kingdom	15	1.3k 0.8×	588 0.8×	414 1.1×	179 0.5×	177 0.5×	31	1.9k
Zhenhai Guo China	15	1.6k 0.9×	612 0.8×	488 1.3×	460 1.3×	318 0.9×	30	2.0k
Ye Ren Singapore	12	1.3k 0.7×	899 1.2×	135 0.4×	451 1.3×	229 0.7×	31	2.4k
Zhu Duan China	24	962 0.6×	430 0.6×	213 0.6×	261 0.7×	553 1.6×	49	1.7k
Shuang Han China	23	1.7k 1.0×	650 0.9×	664 1.7×	148 0.4×	180 0.5×	75	2.2k

Countries citing papers authored by Xiwei Mi

Since Specialization

Citations

This map shows the geographic impact of Xiwei Mi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiwei Mi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiwei Mi more than expected).

Fields of papers citing papers by Xiwei Mi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiwei Mi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiwei Mi. The network helps show where Xiwei Mi may publish in the future.

Co-authorship network of co-authors of Xiwei Mi

This figure shows the co-authorship network connecting the top 25 collaborators of Xiwei Mi. A scholar is included among the top collaborators of Xiwei Mi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiwei Mi. Xiwei Mi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Han, Mei, et al.. (2025). A vulnerability assessment with freight flow data of railway freight transportation network in Northeast China. Journal of Transport Geography. 129. 104416–104416.

Xu, Mingrui, R. Y. Zhu, Chengming Yu, & Xiwei Mi. (2025). DHGAR: Multi-Variable-Driven Wind Power Prediction Model Based on Dynamic Heterogeneous Graph Attention Recurrent Network. Applied Sciences. 15(4). 1862–1862.

Yu, Fuhao, et al.. (2025). Distributed Traffic Signal Control Model for Accurate Policy Learning Under Dynamic Traffic Flow: A Graph Forecast-State Vector Driven Deep Reinforcement Learning Framework. IEEE Transactions on Intelligent Transportation Systems. 26(9). 13573–13584. 1 indexed citations

Mi, Xiwei, et al.. (2025). Durability design of reinforced concrete bridges using time-dependent reliability. Proceedings of the Institution of Civil Engineers - Bridge Engineering. 1–18.

Chen, Chao, et al.. (2024). TFEformer: A new temporal frequency ensemble transformer for day-ahead photovoltaic power prediction. Journal of Cleaner Production. 448. 141690–141690. 21 indexed citations

Yu, Chengqing, et al.. (2024). MRIformer: A multi-resolution interactive transformer for wind speed multi-step prediction. Information Sciences. 661. 120150–120150. 14 indexed citations

Shi, Ziyi, et al.. (2024). WGformer: A Weibull-Gaussian Informer based model for wind speed prediction. Engineering Applications of Artificial Intelligence. 131. 107891–107891. 24 indexed citations

Yu, Chengqing, et al.. (2023). An ensemble convolutional reinforcement learning gate network for metro station PM2.5 forecasting. Stochastic Environmental Research and Risk Assessment. 39(10). 4195–4210. 8 indexed citations

Yu, Chengqing, Guangxi Yan, Chengming Yu, & Xiwei Mi. (2023). Attention mechanism is useful in spatio-temporal wind speed prediction: Evidence from China. Applied Soft Computing. 148. 110864–110864. 32 indexed citations

10.

Mi, Xiwei, et al.. (2022). A dynamic ensemble deep deterministic policy gradient recursive network for spatiotemporal traffic speed forecasting in an urban road network. Digital Signal Processing. 129. 103643–103643. 19 indexed citations

11.

Huang, Li, et al.. (2022). Wind-speed prediction model based on variational mode decomposition, temporal convolutional network, and sequential triplet loss. Sustainable Energy Technologies and Assessments. 52. 101980–101980. 26 indexed citations

12.

Yu, Chengqing, Guangxi Yan, Chengming Yu, Yu Zhang, & Xiwei Mi. (2022). A multi-factor driven spatiotemporal wind power prediction model based on ensemble deep graph attention reinforcement learning networks. Energy. 263. 126034–126034. 99 indexed citations

13.

Yan, Guangxi, et al.. (2021). Sentiment Analysis of Online Course Evaluation Based on a New Ensemble Deep Learning Mode: Evidence from Chinese. Applied Sciences. 11(23). 11313–11313. 10 indexed citations

14.

Mi, Xiwei & Shuo Zhao. (2020). Wind speed prediction based on singular spectrum analysis and neural network structural learning. Energy Conversion and Management. 216. 112956–112956. 83 indexed citations

15.

Zhao, Shuo & Xiwei Mi. (2019). A Novel Hybrid Model for Short-Term High-Speed Railway Passenger Demand Forecasting. IEEE Access. 7. 175681–175692. 15 indexed citations

16.

Liu, Hui, Xiwei Mi, Yanfei Li, Zhu Duan, & Yinan Xu. (2019). Smart wind speed deep learning based multi-step forecasting model using singular spectrum analysis, convolutional Gated Recurrent Unit network and Support Vector Regression. Renewable Energy. 143. 842–854. 162 indexed citations

17.

Liu, Hui, Xiwei Mi, & Yanfei Li. (2018). Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM. Energy Conversion and Management. 159. 54–64. 387 indexed citations breakdown →

18.

Liu, Hui, Xiwei Mi, & Yanfei Li. (2018). Smart deep learning based wind speed prediction model using wavelet packet decomposition, convolutional neural network and convolutional long short term memory network. Energy Conversion and Management. 166. 120–131. 258 indexed citations

19.

Liu, Hui, Xiwei Mi, & Yanfei Li. (2017). Comparison of two new intelligent wind speed forecasting approaches based on Wavelet Packet Decomposition, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Artificial Neural Networks. Energy Conversion and Management. 155. 188–200. 122 indexed citations

20.

Liu, Hui, Xiwei Mi, & Yan-fei Li. (2017). Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network. Energy Conversion and Management. 156. 498–514. 385 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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